CITATION.cff

cff-version: 1.2.0
title: "Efficient scaling and squaring method for the matrix exponential"
message: "If you use this software in your work, please cite it using the following metadata."
date-released: 2024-04-19
authors:
- given-names: "Sergio"
  family-names: "Blanes"
  affiliation: "Universitat Politècnica de València"
  orcid: "https://orcid.org/0000-0001-5819-8898"
- given-names: "Nikita"
  family-names: "Kopylov"
  affiliation: "Universitat Politècnica de València"
  orcid: "https://orcid.org/0000-0002-5557-0858"
- given-names: "Muaz"
  family-names: "Seydaoğlu"
  affiliation: "Muş Alparslan University"
  orcid: "https://orcid.org/0000-0003-3211-0864"
abstract: "This work presents a new algorithm to compute the matrix exponential within a given tolerance. Combined with the scaling and squaring procedure, the algorithm incorporates Taylor, partitioned and classical Padé methods shown to be superior in performance to the approximants used in state-of-the-art software. The algorithm computes matrix--matrix products and also matrix inverses, but it can be implemented to avoid the computation of inverses, making it convenient for some problems. If the matrix A belongs to a Lie algebra, then exp(A) belongs to its associated Lie group, being a property which is preserved by diagonal Padé approximants, and the algorithm has another option to use only these. Numerical experiments show the superior performance with respect to state-of-the-art implementations."
version: 0.1.0
preferred-citation:
  type: article
  title: "Efficient scaling and squaring method for the matrix exponential"
  authors:
  - given-names: "Sergio"
    family-names: "Blanes"
    affiliation: "Universitat Politècnica de València"
    orcid: "https://orcid.org/0000-0001-5819-8898"
  - given-names: "Nikita"
    family-names: "Kopylov"
    affiliation: "Universitat Politècnica de València"
    orcid: "https://orcid.org/0000-0002-5557-0858"
  - given-names: "Muaz"
    family-names: "Seydaoğlu"
    affiliation: "Muş Alparslan University"
    orcid: "https://orcid.org/0000-0003-3211-0864"
  year: 2024